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[1]宋 剑,蒋 瑜,李 冬,等.基于二进制链表的粗糙集属性约简[J].成都信息工程大学学报,2019,(02):112-117.[doi:10.16836/j.cnki.jcuit.2019.02.002]
 SONG Jian,JIANG Yu,LI Dong,et al.Attribute Reduction with Rough Set based on Binary Linked List[J].Journal of Chengdu University of Information Technology,2019,(02):112-117.[doi:10.16836/j.cnki.jcuit.2019.02.002]
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基于二进制链表的粗糙集属性约简

参考文献/References:

[1] Pawlak Z.Rough Sets[J].International Journal of Computer and In-formation Sciences,1982,11:341-356.
[2] Slowinski R.Intelligent decision support-handbook of applications and advances of the rough sets theory[M].London:Kluwer Academic Publishers,1992.
[3] Yunge Jing,Tianrui Li,Hamido Fujita,et al.An incremental attribute reduction method for dynamic data mining[J].Information Sciences,2018,465:202-218.
[4] Yunge Jing,Tianrui Li,Junfu Huang,et al.A Group Incremental Reduction Algorithm with Varying Data Values[J].International Journal of Intelligent Systems,2017,32(9):900-925.
[5] Yunge Jing,Tianrui Li,Hamido Fujita,et al.An incremental attribute reduction approach based on knowledge granularity with a multi-granulation view[J].Information Sciences,2017,411:23-38.
[6] Yunge Jing,Tianrui Li,Junfu Huang,et al.An incremental attribute reduction approach based on knowledge granularity under the attribute generalization[J].International Journal of Approximate Reasoning,2016,76:80-95.
[7] Hongmei Chen,Tianrui Li,Yong Cai,et al.Parallel attribute reduction in dominance-based neighborhood rough set[J].Information Sciences,2016,373:351-368.
[8] Wen S D,Bao Q H.A fast heuristic attribute reduction approach to ordered decision systems[J].European Journal of Operational Research,2018,264:440-452.
[9] Skowron A,Rauszer C.The discernibility matrices and functions in information systems[C].Intelligent Decision Support,Handbook of Applications and Advances of the Rough Sets Theory.Dordrecht,1991:331-362.
[10] 徐章艳,杨炳儒,宋威.基于简化差别矩阵的完备属性约简算法[J].计算机工程与应用,2006,26(3):167-169. [11] 周建华,徐章艳,章晨光.改进的差别矩阵的快速属性约简算法[J].小型微型计算机系统,2014,35(4):831-834.
[12] Felix R,Ushio T.Rough sets-based machine learning using a binary discernibility matrix[C].Proceeding of 2nd International Conference on Intelligent Processing and Manufacturing of Materials,Ha-waii,1999:299-305.
[13] 蒙祖强,史忠植.一种新的基于简化二进制可辨矩阵的相对约简算法[J].控制与决策,2008,23(9):976-978.
[14] 王亚琦,范年柏.改进的基于简化二进制分辨矩阵的属性约简方法[J].计算机科学,2015,42(6):210-215.
[15] Yang M,Yang P.A novel condensing tree structure for rough set feature selection[J].Neurocomputing,2008,71(4):1092-1100.
[16] 蒋瑜.基于差别信息树的rough set属性约简算法[J].控制与决策,2015,30(8):1531-1536.
[17] 张文阳,蒋瑜.基于键树的粗糙集属性约简算法[J].成都信息工程大学学报,2017,32(6):618-622.
[18] 唐坤剑,容强.基于加权浓缩树的粗糙集属性约简算法[J].计算机工程与应用,2018,54(2):76-81.
[19] 梅红岩,刘井莲,刘海霞. 基于区分链表的属性约简改进算法[J]. 计算机与信息技术,2008,(Z1):55-56.
[20] 陈炼,吴灵芝.基于链表的不完备决策表属性约简算法[J].科学技术与工程,2015,15(3):250.

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备注/Memo

收稿日期:2018-09-04 基金项目:四川省教育厅重点资助项目(17ZA0071)

更新日期/Last Update: 2019-05-30